The impact of time-window bias on the assessment of the long-term effect of medication adherence: the case of secondary prevention after myocardial infarction.

Objectives: Time-window bias was described in case-control studies and led to a biased estimate of drug effect. No studies have measured the impact of this bias on the assessment of the effect of medication adherence on health outcomes. Our goals were to estimate the association between adherence to drug therapies after myocardial infarction (MI) and the incidence of a new MI, and to quantify the error that would have been produced by a time-window bias.
Setting: This is a population-based study. Data were obtained from the Regional Health Information Systems of the Lazio Region in Central Italy (around 5 million inhabitants).
Participants: Patients discharged after MI in 2006-2007 were enrolled in the cohort and followed through 2009.
Outcome Measure: The study outcome was reinfarction: either mortality, or hospital admission for MI, whichever occurred first.
Design: A nested case-control study was performed. Controls were selected using both time-dependent and time-independent sampling. Adherence to antiplatelets, β-blockers, ACE inhibitors/angiotensin receptor blockers (ACEI/ARBs) and statins was calculated using the proportion of days covered (PDC).
Results: A total of 6880 patients were enrolled in the cohort. Using time-dependent sampling, a protective effect was detected for all study drugs. Conversely, using time-independent sampling, the beneficial effect was attenuated, as in the case of antiplatelet agents and statins, or completely masked, as in the case of ACEI/ARBs and β-blockers. For ACEI/ARBs, the time-dependent approach produced ORs of 0.83 (95% CI 0.57 to 1.21) and 0.72 (0.55 to 0.95), respectively, for '0.5 < PDC ≤ 0.75' and 'PDC>0.75' versus '0 ≤ PDC ≤ 0.5'. Using the time-independent approach, the ORs were 0.96 (0.65 to 1.43) and 1.00 (0.76 to 1.33), respectively.
Conclusions: A time-independent definition of a time-dependent exposure introduces a bias when the length of follow-up varies with the outcome. The persistence of time-related biases in peer-reviewed papers strongly suggests the need for increased awareness of this methodological pitfall.
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